# US 2020/0401226 A1 · Brain-computer interface method and system based on real-time closed loop vibration stimulation enhancement > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2020/0401226 A1 - Document ID: US20200401226A1 - Status: Published application - Kind: A1 - Application number: 16/977,751 - Filed: 2019-03-21 - Published: 2020-12-24 - Earliest claimed: 2018-12-19 - Assignees: Southeast University - Applicants: Southeast University - Inventors: Aiguo SONG; Wenbin ZHANG; Hong ZENG; Baoguo XU - Web page: https://patentgrep.com/patent/US20200401226A1 ## CPC - G06F 3/015: {Input arrangements based on nervous system activity detection, e.g. brain waves [EEG] detection, electromyograms [EMG] detection, electrodermal response detection} - A61B 5/374: Detecting the frequency distribution of signals, e.g. detecting delta, theta, alpha, beta or gamma waves - A61B 5/375: using biofeedback - A61B 5/378: Visual stimuli - A61B 5/7257: {using Fourier transforms} - A61B 5/7455: {characterised by tactile indication, e.g. vibration or electrical stimulation} - G06F 3/016: {Input arrangements with force or tactile feedback as computer generated output to the user} - G06F 17/142: {Fast Fourier transforms, e.g. using a Cooley-Tukey type algorithm} - G06F 2203/011: Emotion or mood input determined on the basis of sensed human body parameters such as pulse, heart rate or beat, temperature of skin, facial expressions, iris, voice pitch, brain activity patterns - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D) ## Abstract The present invention discloses a brain-computer interface method and system based on real-time closed loop vibration stimulation enhancement. The method includes: displaying and providing a motor imagery task to a subject, and collecting a generated digital electroencephalogram signal; reading the digital electroencephalogram signal, judging whether a preset time period is exceeded or not, performing interception if YES, and performing continuous reading if NO; performing band-pass filtering, obtaining time-frequency characteristics of the digital electroencephalogram signal through calculation by fast Fourier transform, and extracting a frequency value with highest frequency energy as a main frequency; obtaining an instantaneous phase of the digital electroencephalogram signal through calculation by Hilbert transform; generating predicted sine waves by respectively using the main frequency and the instantaneous phase as a frequency and an initial phase of sine waves, and predicting and obtaining real-time phase information; and judging whether the real-time phase is in a vibration stimulation application phase interval or not, generating and outputting a control instruction, and controlling a vibration motor to vibrate and to stimulate a sensory channel of the subject according to the control instruction. The present invention improves a signal-to-noise ratio of a brain-computer interface system, and enhances a recognition rate of a motor imagery signal. ## Claims ### Claim 1 A brain-computer interface method based on real-time closed loop vibration stimulation enhancement, comprising the following steps: displaying and providing a motor imagery task to a subject, and collecting a digital electroencephalogram signal of the subject generated during motor imagery; reading the collected digital electroencephalogram signal, judging whether a preset time period is exceeded or not, intercepting the digital electroencephalogram signal in the preset time period if YES, and continuously reading the collected digital electroencephalogram signal if NO; after band-pass filtering is performed on the intercepted digital electroencephalogram signal in the preset time period, obtaining time-frequency characteristics of the digital electroencephalogram signal of the period through calculation by fast Fourier transform, and extracting a frequency value with highest frequency energy as a main frequency; obtaining an instantaneous phase of the digital electroencephalogram signal of the period through calculation by Hilbert transform on the digital electroencephalogram signal subjected to band-pass filtering; generating predicted sine waves by respectively using the main frequency and the instantaneous phase of the digital electroencephalogram signal of the period as a frequency and an initial phase of sine waves, and predicting and obtaining real-time phase information at the current moment according to the predicted sine waves; and judging whether the real-time phase is in a vibration stimulation application phase interval or not according to the predicted and obtained real-time phase information at the current moment, generating and outputting a control instruction according to the judging result, and controlling a vibration motor to vibrate and to stimulate a sensory channel of the subject according to the control instruction. ### Claim 2 (depends on 1) The brain-computer interface method based on real-time closed loop vibration stimulation enhancement according to claim 1, wherein the motor imagery task in the method comprises a left-hand or right-hand motor imagery action. ### Claim 3 (depends on 1) The brain-computer interface method based on real-time closed loop vibration stimulation enhancement according to claim 1, wherein in the method, the intercepted digital electroencephalogram signal in the preset time period is subjected to a waveband band-pass filtering. ### Claim 4 (depends on 1) The brain-computer interface method based on real-time closed loop vibration stimulation enhancement according to claim 1, wherein for obtaining the instantaneous phase of the digital electroencephalogram signal through calculation by Hilbert transform in the method, the following formulas are used: y ( t ) = p · 1 π · v · ∫ - ∞ + ∞  x ( t ) t - τ  d   τ ; and θ x  ( t ) = tan - 1  y  ( t ) x  ( t ) , wherein y(t) is a digital electroencephalogram signal after Hilbert transform is performed on x(t); x(t) is the digital electroencephalogram signal after the band-pass filtering; p and v are integrals in the Cauchy principal value sense; and θx(t) is an instantaneous phase at a moment t. ### Claim 5 (depends on 1) The brain-computer interface method based on real-time closed loop vibration stimulation enhancement according to claim 1, wherein the predicted sine wave fs generated in the method is specifically: f s = sin  ( 2 · π · f main · t f + θ   x  ( t ) + π 2 ) , wherein fmain is a main frequency of the intercepted digital electroencephalogram signal of the preset time period; tf is a length of a predicted waveform, and θx(t) is an instantaneous phase at the moment t. ### Claim 6 A brain-computer interface system based on real-time closed loop vibration stimulation enhancement, comprising: a human-computer interaction module, configured to display and provide a motor imagery task to a subject; an electroencephalogram signal collection module, configured to collect a digital electroencephalogram signal generated during motor imagery of the subject; a real-time phase prediction module, configured to read the collected digital electroencephalogram signal, judge whether the preset time period is exceeded or not, intercept the digital electroencephalogram signal in the preset time period if YES, and continuously read the collected digital electroencephalogram signal if NO; and configured to obtain time-frequency characteristics of the digital electroencephalogram signal of the period through calculation by fast Fourier transform after performing band-pass filtering on the intercepted digital electroencephalogram signal in the preset time period, extract a frequency value with highest frequency energy in the time-frequency characteristics as its main frequency, obtain an instantaneous phase of the digital electroencephalogram signal of the period through calculation by Hilbert transform, generate predicted sine waves by respectively using the main frequency and the instantaneous phase of the digital electroencephalogram signal of the period as a frequency and an initial phase of sine waves, and predict and obtain real-time phase information at the current moment according to the predicted sine waves; an electroencephalogram signal analysis module, configured to judge whether the real-time phase is in a vibration stimulation application phase interval or not according to the predicted and obtained real-time phase information at the current moment, and generate and output a control instruction according to the judging result; and a vibration stimulation feedback module, configured to control a vibration motor to vibrate and to stimulate a sensory channel of the subject according to the control instruction output by the electroencephalogram signal analysis module. ### Claim 7 (depends on 6) The brain-computer interface method based on real-time closed loop vibration stimulation enhancement according to claim 6, wherein the electroencephalogram signal collection module comprises an electroencephalogram cap, an electroencephalogram signal amplifier, a low-pass and band-stop filter, an analog-to-digital conversion module and a communication module in sequential connection. ### Claim 8 (depends on 6) The brain-computer interface method based on real-time closed loop vibration stimulation enhancement according to claim 6, wherein the real-time phase prediction module uses a band-pass filter to perform band-pass filtering on the digital electroencephalogram signal in the preset time period. ### Claim 9 (depends on 8) The brain-computer interface method based on real-time closed loop vibration stimulation enhancement according to claim 8, wherein the band-pass filter adopts a ten-order oval infinite impulse response filter. ### Claim 10 (depends on 6) The brain-computer interface method based on real-time closed loop vibration stimulation enhancement according to claim 6, wherein the vibration stimulation feedback module sets different vibration frequencies to act on the left hand and the right hand according to the control instruction.